Before you begin

This tutorial assumes that you have already followed the steps in Installing Pyramid, except do not create a virtual environment or install Pyramid. Thereby you will satisfy the following requirements.

Install SQLite3 and its development packages

If you used a package manager to install your Python or if you compiled your Python from source, then you must install SQLite3 and its development packages. If you downloaded your Python as an installer from, then you already have it installed and can skip this step.

If you need to install the SQLite3 packages, then, for example, using the Debian system and apt-get, the command would be the following:

$ sudo apt-get install libsqlite3-dev

Install cookiecutter

We will use a cookiecutter to create a Python package project from a Python package project template. See Cookiecutter Installation for instructions.

Generate a Pyramid project from a cookiecutter

We will create a Pyramid project in your home directory for UNIX or at the root for Windows. It is assumed you know the path to where you installed cookiecutter. Issue the following commands and override the defaults in the prompts as follows.


$ cd ~
$ cookiecutter gh:Pylons/pyramid-cookiecutter-alchemy --checkout 1.9-branch

On Windows

c:\> cd \
c:\> cookiecutter gh:Pylons/pyramid-cookiecutter-alchemy --checkout 1.9-branch

On all operating systems

If prompted for the first item, accept the default yes by hitting return.

You've cloned ~/.cookiecutters/pyramid-cookiecutter-alchemy before.
Is it okay to delete and re-clone it? [yes]: yes
project_name [Pyramid Scaffold]: myproj
repo_name [myproj]: tutorial

Change directory into your newly created project


$ cd tutorial

On Windows

c:\> cd tutorial

Set and use a VENV environment variable

We will set the VENV environment variable to the absolute path of the virtual environment, and use it going forward.


$ export VENV=~/tutorial

On Windows

c:\tutorial> set VENV=c:\tutorial

Create a virtual environment


$ python3 -m venv $VENV

On Windows

Each version of Python uses different paths, so you will need to adjust the path to the command for your Python version. Recent versions of the Python 3 installer for Windows now install a Python launcher.

Python 2.7:

c:\tutorial> c:\Python27\Scripts\virtualenv %VENV%

Python 3.6:

c:\tutorial> python -m venv %VENV%

Upgrade packaging tools in the virtual environment


$ $VENV/bin/pip install --upgrade pip setuptools

On Windows

c:\tutorial> %VENV%\Scripts\pip install --upgrade pip setuptools

Installing the project in development mode

In order to do development on the project easily, you must "register" the project as a development egg in your workspace. We will install testing requirements at the same time. We do so with the following command.


$ $VENV/bin/pip install -e ".[testing]"

On Windows

c:\tutorial> %VENV%\Scripts\pip install -e ".[testing]"

On all operating systems

The console will show pip checking for packages and installing missing packages. Success executing this command will show a line like the following:

Successfully installed Jinja2-2.8 Mako-1.0.6 MarkupSafe-0.23 \
PasteDeploy-1.5.2 Pygments-2.1.3 SQLAlchemy-1.1.4 WebOb-1.6.3 \
WebTest-2.0.24 beautifulsoup4-4.5.1 coverage-4.2 py-1.4.32 pyramid-1.7.3 \
pyramid-debugtoolbar-3.0.5 pyramid-jinja2-2.7 pyramid-mako-1.0.2 \
pyramid-tm-1.1.1 pytest-3.0.5 pytest-cov-2.4.0 repoze.lru-0.6 six-1.10.0 \
transaction-2.0.3 translationstring-1.3 tutorial venusian-1.0 \
waitress-1.0.1 zope.deprecation-4.2.0 zope.interface-4.3.3 \

Testing requirements are defined in our project's file, in the tests_require and extras_require stanzas.

tests_require = [
    'WebTest >= 1.3.1',  # py3 compat
        'testing': tests_require,

Run the tests

After you've installed the project in development mode as well as the testing requirements, you may run the tests for the project. The following commands provide options to py.test that specify the module for which its tests shall be run, and to run py.test in quiet mode.


$ $VENV/bin/py.test -q

On Windows

c:\tutorial> %VENV%\Scripts\py.test -q

For a successful test run, you should see output that ends like this:

2 passed in 0.44 seconds

Expose test coverage information

You can run the py.test command to see test coverage information. This runs the tests in the same way that py.test does, but provides additional coverage information, exposing which lines of your project are covered by the tests.

We've already installed the pytest-cov package into our virtual environment, so we can run the tests with coverage.


$ $VENV/bin/py.test --cov --cov-report=term-missing

On Windows

c:\tutorial> %VENV%\Scripts\py.test --cov --cov-report=term-missing

If successful, you will see output something like this:

======================== test session starts ========================
platform Python 3.6.0, pytest-3.0.5, py-1.4.31, pluggy-0.4.0
rootdir: /Users/stevepiercy/tutorial, inifile:
plugins: cov-2.4.0
collected 2 items

tutorial/ ..
------------------ coverage: platform Python 3.6.0 ------------------
Name                               Stmts   Miss  Cover   Missing
tutorial/                   8      6    25%   7-12
tutorial/models/           22      0   100%
tutorial/models/                5      0   100%
tutorial/models/             8      0   100%
tutorial/                     3      2    33%   2-3
tutorial/scripts/           0      0   100%
tutorial/scripts/      26     16    38%   22-25, 29-45
tutorial/views/             0      0   100%
tutorial/views/             12      0   100%
tutorial/views/             4      2    50%   6-7
TOTAL                                 88     26    70%
===================== 2 passed in 0.57 seconds ======================

Our package doesn't quite have 100% test coverage.

Test and coverage cookiecutter defaults

Cookiecutters include configuration defaults for py.test and test coverage. These configuration files are pytest.ini and .coveragerc, located at the root of your package. Without these defaults, we would need to specify the path to the module on which we want to run tests and coverage.


$ $VENV/bin/py.test --cov=tutorial tutorial/ -q

On Windows

c:\tutorial> %VENV%\Scripts\py.test --cov=tutorial tutorial\ -q

py.test follows conventions for Python test discovery, and the configuration defaults from the cookiecutter tell py.test where to find the module on which we want to run tests and coverage.

See also

See py.test's documentation for Usage and Invocations or invoke py.test -h to see its full set of options.

Initializing the database

We need to use the initialize_tutorial_db console script to initialize our database.


The initialize_tutorial_db command does not perform a migration, but rather it simply creates missing tables and adds some dummy data. If you already have a database, you should delete it before running initialize_tutorial_db again.

Type the following command, making sure you are still in the tutorial directory (the directory with a development.ini in it):


$ $VENV/bin/initialize_tutorial_db development.ini

On Windows

c:\tutorial> %VENV%\Scripts\initialize_tutorial_db development.ini

The output to your console should be something like this:

2016-12-18 21:30:08,675 INFO  [sqlalchemy.engine.base.Engine:1235][MainThread] SELECT CAST('test plain returns' AS VARCHAR(60)) AS anon_1
2016-12-18 21:30:08,675 INFO  [sqlalchemy.engine.base.Engine:1236][MainThread] ()
2016-12-18 21:30:08,676 INFO  [sqlalchemy.engine.base.Engine:1235][MainThread] SELECT CAST('test unicode returns' AS VARCHAR(60)) AS anon_1
2016-12-18 21:30:08,676 INFO  [sqlalchemy.engine.base.Engine:1236][MainThread] ()
2016-12-18 21:30:08,676 INFO  [sqlalchemy.engine.base.Engine:1140][MainThread] PRAGMA table_info("models")
2016-12-18 21:30:08,676 INFO  [sqlalchemy.engine.base.Engine:1143][MainThread] ()
2016-12-18 21:30:08,677 INFO  [sqlalchemy.engine.base.Engine:1140][MainThread]
        id INTEGER NOT NULL,
        name TEXT,
        value INTEGER,
        CONSTRAINT pk_models PRIMARY KEY (id)

2016-12-18 21:30:08,677 INFO  [sqlalchemy.engine.base.Engine:1143][MainThread] ()
2016-12-18 21:30:08,678 INFO  [sqlalchemy.engine.base.Engine:719][MainThread] COMMIT
2016-12-18 21:30:08,679 INFO  [sqlalchemy.engine.base.Engine:1140][MainThread] CREATE UNIQUE INDEX my_index ON models (name)
2016-12-18 21:30:08,679 INFO  [sqlalchemy.engine.base.Engine:1143][MainThread] ()
2016-12-18 21:30:08,679 INFO  [sqlalchemy.engine.base.Engine:719][MainThread] COMMIT
2016-12-18 21:30:08,681 INFO  [sqlalchemy.engine.base.Engine:679][MainThread] BEGIN (implicit)
2016-12-18 21:30:08,682 INFO  [sqlalchemy.engine.base.Engine:1140][MainThread] INSERT INTO models (name, value) VALUES (?, ?)
2016-12-18 21:30:08,682 INFO  [sqlalchemy.engine.base.Engine:1143][MainThread] ('one', 1)
2016-12-18 21:30:08,682 INFO  [sqlalchemy.engine.base.Engine:719][MainThread] COMMIT

Success! You should now have a tutorial.sqlite file in your current working directory. This is an SQLite database with a single table defined in it (models).

Start the application

Start the application. See What Is This pserve Thing for more information on pserve.


$ $VENV/bin/pserve development.ini --reload

On Windows

c:\tutorial> %VENV%\Scripts\pserve development.ini --reload


Your OS firewall, if any, may pop up a dialog asking for authorization to allow python to accept incoming network connections.

If successful, you will see something like this on your console:

Starting subprocess with file monitor
Starting server in PID 44078.
Serving on http://localhost:6543
Serving on http://localhost:6543

This means the server is ready to accept requests.

Visit the application in a browser

In a browser, visit http://localhost:6543/. You will see the generated application's default page.

One thing you'll notice is the "debug toolbar" icon on right hand side of the page. You can read more about the purpose of the icon at The Debug Toolbar. It allows you to get information about your application while you develop.

Decisions the alchemy cookiecutter has made for you

Creating a project using the alchemy cookiecutter makes the following assumptions:


Pyramid supports any persistent storage mechanism (e.g., object database or filesystem files). It also supports an additional mechanism to map URLs to code (traversal). However, for the purposes of this tutorial, we'll only be using URL dispatch and SQLAlchemy.